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A method to assess and support exploitation projects of university researchers

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Abstract

Assessing the exploitation potential of university research is needed to improve the efficiency of a Technology Transfer Office (TTO) and to increase chances of picking up and supporting viable entrepreneurial projects. The paper proposes an assessment method that jointly looks into the technology and the commercialization perspectives of research exploitation projects. The commercialization perspectives are further subdivided to criteria characterizing the market opportunities and management team. The method is applied to an ad hoc TTO in the Agricultural University of Athens (AUA). In addition to selecting exploitation projects proposed by AUA researchers, the method is also used to design support services for the research teams during the commercialization process. Relating the assessment outcome to the support of exploitation is a topic that received limited attention so far. In the case of universities that are about to start investing in technology transfer, the proposed approach can assist management to define strategies and corresponding services for academic entrepreneurship that are in line with the organization’s research profile. For more mature technology transfer environments, the method can be used to diversify the services of the TTO, by including forms of interaction with industry and businesses better serving the research community.

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Notes

  1. According to JRC (2012), smart specialisation is “…a process of developing a vision, identifying the place-based areas of greatest strategic potential, developing multi-stakeholder governance mechanisms, setting strategic priorities and using smart policies to maximize the knowledge-based development potential of a region, regardless of whether it is strong or weak, high-tech or low-tech”. The origins of the concept can be traced to a number of complementary sources, of which the work reported in Foray et al. (2009).

  2. Based on figures provided by the Association of University Technology Managers, Bradley et al. (2013) reported that the number of full-time employees of American TTOs increased from about 500 in the early 90s’ to close to 2000 in 2010. In a survey conducted in 2007, the average number of staff in European TTOs was found to be 10.9 professionals (Conti and Gaule 2008). Today it is common to find European TTOs with as many as 50–100 staff, especially in Universities that are particularly active in innovation and commercialisation of research, for example those reported in Trueman et al. (2014).

  3. The project was funded by the City of Athens as a component of a regional development programme. One of the broader objectives was to promote the participation of Higher Education Institutions to initiatives aiming to stimulate competitiveness and economic growth, in agreement with the smart specialization approach referred to above.

  4. Put simply, providing advice to a university researcher to create a startup calls for different qualifications and skills for the TTO to the ones required when assisting a research team to launch university–industry cooperation through research contracts, clustering, or other forms of interaction that facilitate open innovation approaches.

  5. As reported in the literature, TTOs and university licensing offices implement different methods to evaluate technologies, but since they usually operate in a cruising mode handling proposals in moderate numbers, only a few of them use a methodology of a standard evaluation process (14 out of 100 surveyed of top TTO’s in the US, Hallam et al. 2011). We could not find any literature related to how such evaluations are linked to the organization of TTO support.

  6. An indication of the international orientation of AUA’s staff can be provided by looking into the countries where they obtained their PhD. 55% got their PhDs in Greek Universities (41% in AUA). The remaining 45% received their PhD in UK: 19%, USA: 13%, France: 5%, Germany 4%, other countries: 4%.

  7. In this period there have been 1, 69 and 130 papers from AUA in respectively the top 1, 10 and 25% most influential.

  8. Data on number of publications, number of citations and relative citation impact are taken from Sahini (2014).

  9. A manual search was done on the full list of AUA staff using the European Patent Office (EPO) online service, Espacenet. Espacenet contains information on patents and patent applications for more than 90 countries. As discussed in Drivas et al. 2016, matches have been further cross-checked to see if the inventor had disclosed a Greek address and whether the technology field of the patent was similar to his/her area of specialization.

  10. The figure is even lower if single applicants are considered: in fact, the 28 patent applications have been filed by 11 researchers, meaning that 94% of the research staff have not been involved in any patenting activity from 2002 to 2013.

  11. In two cases, researchers that submitted two complementary proposals followed the recommendation of the project team to merge their submissions into one with increased commercialization potential. As a result, the number of proposals that followed the complete assessment cycle came to a total of 40.

  12. Research contracts comprise research and technological development grants from the European Commission and the Greek government, as well as projects commissioned by Greek public and private organizations.

  13. The two populations have very close distributions of their members across the four faculty ranks (full professor, associate professor, assistant professor and lecturer), meaning that comparisons should not be biased by differences in terms of seniority in the two populations.

  14. TRL was introduced by NASA in the 1980’s and subsequently adopted by other research Institutions (EARTO 2014). The form presented in Table 3 follows the one in European Commission (2015).

  15. A detailed description of how TRL can be used to guide an inventor’s strategy in the different steps of the innovation process is presented in Vekinis (2014).

  16. In view of the very limited patenting activity in AUA, it was decided not to include a criterion on the existence or not of a patent. As indicated in Sects. 3.3 and 4.3, the assessment looked into IPR and other legal/environmental aspects and formulated recommendations for actions in these fields.

  17. Vinig and Lips (2015) state that technology transfer performance of a university should be measured against the potential for technology transfer, which they propose to link to the organization’s research output. In their method, the actual valorization output (AVP), being the sum of patents, spinoffs and licensing agreements on a yearly basis, is compared to the Potential Valorization Projects (PVP), taken to be equal to the total number of journal publications times a valorization coefficient that is assumed to range from 1 to 3%. Technology transfer performance is good (equivalently, poor), if AVP is larger (equivalently, lower) than PVP. In view of the current journal publication figures of AUA reported in Sect. 2, the PVP would range from 3 to 9 projects achieving their exploitation target.

  18. Given the limited experience of AUA researchers in IP it was decided to approach the IP question by asking technology assessors to comment on the most appropriate IP strategies to be adopted—see also footnote 16.

  19. As pointed out in Vekinis (2014), it s imperative to decide on the ability to effectively protect a technology and its patentability, before undertaking the laboratory validation and engaging into even a limited communication with third parties.

References

  • Acs, Z. J., & Audretsch, D. B. (2010). Knowledge spillover entrepreneurship. In Z. J. Acs & D. B. Audretsch (Eds.), Handbook of Entrepreneurship Research, International Handbook Series on Entrepreneurship, Vol. 5. doi:10.1007/978-1-4419-1191-9_11.

  • Audretsch, D. B. (2009). The entrepreneurial society. Journal of Technology Transfer, 3, 245–254.

    Article  Google Scholar 

  • Audretsch, D. B. (2014). From the entrepreneurial university to the university for the entrepreneurial society. Journal of Technology Transfer, 39, 313–321.

    Article  Google Scholar 

  • Bercovitz, J., & Feldman, M. (2006). Entrepreneurial universities and technology transfer: A conceptual framework for understanding knowledge-based economic development. Journal of Technology Transfer, 31, 175–188.

    Article  Google Scholar 

  • Bozeman, B. (2000). Technology transfer and public policy: A review of research and theory. Research Policy, 29, 627–655.

    Article  Google Scholar 

  • Bozeman, B., Rimes, H., & Youtie, J. (2015). The evolving state-of-the-art in technology transfer research: Revisiting the contingent effectiveness model. Research Policy, 44, 34–49.

    Article  Google Scholar 

  • Bradley, S., Hayter, C. S., & Link, A. N. (2013). Models and methods of university technology transfer. The University of North Carolina at Greensboro, Department of Economics Working Paper Series, Working Paper 13–10. http://bae.uncg.edu/assets/research/econwp/2013/13-10.pdf

  • Chesbrough, H. (2003). Open innovation: The new imperative for creating and profiting from technology. Boston: Harvard Business School Press.

    Google Scholar 

  • Conti, A., & Gaule, P. (2008). The CEMI survey of university Technology Transfer Offices in Europe. Ecole Polytechnique Federale de Lausanne. http://cemi.epfl.ch/page-30722-en.html

  • Debackere, K. (2012). The TTO, a university engine transforming science into innovation. League of European Research Universities (LERU), Advice Paper No. 10. http://www.leru.org/files/publications/TTO_paper_final.pdf

  • Debackere, K., & Veugelers, R. (2005). The role of academic technology transfer organizations in improving industry science links. Research Policy, 34(3), 321–342.

    Article  Google Scholar 

  • Drivas, K., Balafoutis, A. T., & Rozakis, S. (2016). Research funding and academic output: Evidence from the Agricultural University of Athens. Prometheus,. doi:10.1080/08109028.2016.1150575.

    Google Scholar 

  • EARTO. (2014). The TRL scale as a research and innovation policy tool. EARTO Recommendations. European Association of Research and Technology Organisations. http://www.earto.eu/fileadmin/content/03_Publications/The_TRL_Scale_as_a_R_I_Policy_Tool_-_EARTO_Recommendations_-_Final.pdf

  • Etzkowitz, H. (2003). Research groups as ‘quasi-firms’: The invention of the entrepreneurial university. Research Policy, 32(1), 109–121.

    Article  Google Scholar 

  • European Commission. (2014). European innovation scoreboard 2013—Comparative analysis of innovation performance. Luxembourg: Office for Official Publications of the European Communities.

    Google Scholar 

  • European Commission. (2015). Horizon 2020 Work Programme 2016–2017, Annex G. European Commission Decision C 6776 of 13 October 2015. http://ec.europa.eu/research/participants/data/ref/h2020/other/wp/2016-2017/annexes/h2020-wp1617-annex-ga_en.pdf

  • Foray, D., David, P. A., & Hall, B. (2009). Smart specialisation—The concept. Knowledge Economists Policy Brief No. 9, pp. 25–29. http://ec.europa.eu/invest-in-research/pdf/download_en/kfg_policy_briefs_no_5_9.pdf.

  • Friedman, J., & Silberman, J. (2003). University technology transfer: Do incentives, management, and location matter? Journal of Technology Transfer, 28, 17–30.

    Article  Google Scholar 

  • Gans, J. S., & Stern, S. (2003). The product market and the market for “ideas”: Commercialization strategies for technology entrepreneurs. Research Policy, 32, 333–350.

    Article  Google Scholar 

  • Guerrero, M., & Urbano, D. (2012). The development of an entrepreneurial university. Journal of Technology Transfer, 37(1), 43–74.

    Article  Google Scholar 

  • Hallam, C. R. A., Leffel, A., Chinea, I. (2011). Early phase technology management valuation practices by university licensing offices in the United States: Empirical data from a survey of the top 100 organizations. In PICMET: Portland International Center for Management of Engineering and Technology, 2011 proceedings of PICMET ‘11: Technology Management in the Energy Smart World (PICMET).

  • Hayter, C. (2013). Harnessing university entrepreneurship for economic growth: Factors of success among university spinoffs. Economic Development Quarterly, 27(1), 18–28.

    Article  Google Scholar 

  • Heinzl, J., Kor, A., Orange, G., & Kaufmann, H. (2008). Technology transfer model for Austrian higher education institutions. Paper presented at the European and mediterranean conference on information systems, May 25–26, 2008.

  • Heslop, L. A., McGregor, E., & Griffith, M. (2001). Development of a technology readiness assessment measure: The cloverleaf model of technology transfer. Journal of Technology Transfer, 26, 369–384.

    Article  Google Scholar 

  • Jain, R. K., Martyniuk, A. O., Harris, M. M., Niermann, R. N., & Woldmann, K. (2003). Evaluating the commercial potential of emerging technologies. International Journal of Technology Transfer and Commercialisation, 2, 32–50.

    Article  Google Scholar 

  • JRC. (2012). Guide on regional/national research and innovation strategies for smart specialisation (RIS 3 ). Brussels: European Commission Joint Research Centre. http://ec.europa.eu/regional_policy/sources/docgener/presenta/smart_specialisation/smart_ris3_2012.pdf

  • JRC. (2014). RIS3 implementation and policy mixes. S3 Policy Brief Series No. 07. Brussels: European Commission Joint Research Centre. http://s3platform.jrc.ec.europa.eu/documents/20182/114990/JRC91917_RIS3_implementation_and_policy_mixes_final.pdf/e56f2977-f217-475c-95c2-649c55d83b40

  • Mavrotas, G., Diakoulaki, D., & Caloghirou, Y. (2006). Project prioritization under policy restrictions. A combination of MCDA with 0–1 programming. European Journal of Operational Research, 171, 296–308.

    Article  Google Scholar 

  • Mohannak, K., & Samtani, L. (2014). A criteria-based approach for evaluating innovation commercialisation. Paper presented at the DRUID Society Conference 2014, CBS, Copenhagen, June 16–18.

  • O’Shea, R. P., Chugh, H., & Allen, T. J. (2008). Determinants and consequences of university spinoff activity: A conceptual framework. Journal of Technology Transfer, 33, 653–666.

    Article  Google Scholar 

  • OECD. (2011). Reviews of regional innovation: Regions and innovation policy. Organisation for Economic Co-operation and Development. Publication date: 04/05/2011. http://www.oecd.org/gov/regional-policy/oecdreviewsofregionalinnovationregionsandinnovationpolicy.htm

  • Oral, M., Kettani, O., & Lang, P. (1991). A methodology for collective evaluation and selection of industrial R&D projects. Management Science, 37, 871–885.

    Article  Google Scholar 

  • Phan, P., Siegel, D., & Wright, M. (2005). Science parks and incubators: Observations, synthesis and future research. Journal of Business Venturing, 20(2), 165–182.

    Article  Google Scholar 

  • Rahal, A. D., & Rabelo, L. C. (2006). Assessment framework for the evaluation and prioritization of university inventions for licencing and commercialization. Engineering Management Journal, 18(4), 28–36.

    Article  Google Scholar 

  • Rothaermel, F., Agung, S., & Jiang, L. (2007). University entrepreneurship: A taxonomy of the literature. Industrial and Corporate Change, 16(4), 691–791.

    Article  Google Scholar 

  • Sahini, E. (2014). Bibliometric analysis of Greek publications in international scientific journals. National Documentation Centre. Publication date: 15 December 2014. http://report04.metrics.ekt.gr/

  • Siegel, D. S. (2011). Academic entrepreneurship: Lessons learned for university administrators and policymakers. Presented at the Strategic Management of Places Conference, December 13, 2011.

  • Siegel, D. S., Veugelers, R., & Wright, M. (2007). Technology Transfer Offices and commercialization of university intellectual property: Performance and policy implications. Oxford Review of Economic Policy, 23(4), 640–660.

    Article  Google Scholar 

  • Thursby, J. G., Jensen, R. A., & Thursby, M. C. (2001). Objectives, characteristics and outcomes of university licensing: A survey of major U.S. universities. Journal of Technology Transfer, 26, 59–70.

    Article  Google Scholar 

  • Thursby, J. G., & Thursby, M. C. (2003). Industry/university licensing: Characteristics, concerns and issues from the perspective of the buyer. Journal of Technology Transfer, 28, 207–213.

    Article  Google Scholar 

  • Thursby, J., & Thursby, M. (2007). Patterns of research and licensing activity of science and engineering faculty. In P. Stephan & R. Ehrenberg (Eds.), Science and the university. Madison: University of Wisconsin Press.

    Google Scholar 

  • Trueman, S., Borrell-Damian, L., & Smith, J. H. (2014). The evolution of university-based knowledge transfer structures. The EUIMA Collaborative Research Project Papers. http://www.eua.be/Libraries/Publications/Stephen_Trueman_Final.sflb.ashx

  • Vekinis, G. (2014). Technology transfer in practice: From invention to innovation. Athens: Presstime. eBook ISBN: 978-960-93-5996-2 and Paperback ISBN: 978-960-93-5855-2.

  • Vinig, T., & Lips, D. (2015). Measuring the performance of university technology transfer using meta data approach: The case of Dutch universities. Journal of Technology Transfer, 40(6), 1034–1049.

    Article  Google Scholar 

  • Young, T. A. (2007). Establishing a Technology Transfer Office. In A. Krattiger, R. T. Mahoney, L. Nelsen, et al. (Eds.), Intellectual property management in health and agricultural innovation: A handbook of best practices. Oxford: MIHR.

    Google Scholar 

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Acknowledgements

Financial support is gratefully acknowledged from the municipality of Athens through the grant innovation and entrepreneurship—valorization of research by the Agricultural University of Athens (Reference 464052).

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Authors and Affiliations

  1. LOGOTECH, 100, Kifisias Avenue and 83, Marathonodromou Street, 151 25, Marousi, Greece

    Odysseas Cartalos & Dominiki Tsiouki

  2. Technical University of Crete, 731 00, Kounoupidiana, Chania, Greece

    Stelios Rozakis

  3. Postgraduate Program MBA in Agribusiness, Agricultural University of Athens, Iera Odos 75, 118 55, Athens, Greece

    Stelios Rozakis

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  1. Odysseas Cartalos
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Cartalos, O., Rozakis, S. & Tsiouki, D. A method to assess and support exploitation projects of university researchers. J Technol Transf 43, 986–1006 (2018). https://doi.org/10.1007/s10961-016-9519-y

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